Sentence examples for selection goodness from inspiring English sources

Likelihood ratio tests were used for model selection, goodness of fit was assessed and model diagnoses were carried out.

There was no statistical difference between the A-G and frailty models when applied to the NRL recurrent injury data analysed in this study in terms of model selection, goodness of fit or accuracy.

Comprehensive model evaluation must include consideration of sample design, covariate selection, goodness-of-fit and parameter redundancy diagnostics.

Basic model-fitting techniques, including variable selection, goodness-of-fit, adjusted generalised R, and regression diagnostics (residual analysis, detection of influential cases, and check for multi-collinearity) were applied to ensure the quality of the multivariate analysis.

Basic model-fitting techniques, including variable selection, goodness-of-fit, area under the receiver operating characteristic curve, adjusted generalized R and regression diagnostics (residual analysis, detection of influential cases, and check for multicollinearity), were applied to assure the quality of the multivariate analysis.

Model selection and goodness-of-fit can be assessed based on information criteria or the likelihood-ratio test statistic [ 28].

To ensure the validity of our results, basic model-fitting techniques for (1) variable selection, (2) goodness-of-fit (GOF) assessment, and (3) regression diagnostics were all used in our regression analyses.

To ensure the quality of analysis results, basic model-fitting techniques for (1) variable selection, (2) goodness-of-fit (GOF) assessment, and (3) regression diagnostics were used in our regression analyses.

In our regression analyses, basic model-fitting techniques for (a) variable selection, (b) goodness-of-fit assessment, and (c) regression diagnostics (including residual analysis, influence analysis, and check of multicollinearity) were used to ensure the quality of the analysis results [ 27, 28].

The basic model-fitting techniques for (1) variable selection, (2) goodness-of-fit assessment, and (3) regression diagnostics (e.g., residual analysis, detection of influential cases, and check for multicollinearity) were used in our regression analyses to ensure the quality of analysis results.

The basic model-fitting techniques for (1) variable selection, (2) goodness-of-fit assessment, and (3) regression diagnostics (e.g., residual analysis, detection of influential cases, and check for multicollinearity) were used in our regression analyzes to ensure the quality of the analysis results.